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AI+ Security Practitioner™
This certification validates foundational knowledge of AI-driven cybersecurity concepts and assesses understanding of security principles, threats, and controls. The exam evaluates competency in applying core cybersecurity knowledge within AI-enabled environments.
Certificate Code
AT-2101
Exam Format
AI-Driven Remote Exam Proctoring
Course Overview
Important details and certification information
Instructor-led OR Self-paced course + Official exam + Digital badge
Instructor-Led: 3 Days (live or virtual)
Basic AI, cybersecurity, networking, security operations, data protection, programming, and responsible AI knowledge.
50 questions, 70% passing, 90 minutes, online proctored exam
Certification Modules
- You will learn about computer systems, operating systems, Linux administration, file systems, commands, user management, permissions, authentication, and access control concepts.
- You will learn networking concepts, IP addressing, protocols, TCP/IP communication, DNS, network security, traffic analysis, firewalls, IDS/IPS, and VPN technologies.
- You will learn Python programming fundamentals and how to use scripting for security automation, log analysis, data processing, and efficient security workflows.
- You will learn cybersecurity principles, risks, vulnerabilities, attack surfaces, security controls, common cyber threats, and industry security frameworks.
- You will learn encryption, hashing, digital signatures, TLS security, authentication methods, identity management, access controls, and identity protection practices.
- You will learn AI, ML, and Deep Learning fundamentals, learning approaches, ML lifecycle, datasets, model evaluation, and AI applications in cybersecurity.
- You will learn AI-based threat detection, behavioral analytics, anomaly detection, threat intelligence, threat hunting, MITRE ATT&CK mapping, and AI-assisted SOC operations.
- You will learn LLMs, Generative AI, AI copilots, RAG, OWASP LLM security risks, AI vulnerabilities, governance, and responsible AI practices.
- You will learn AI threat modeling, attack surfaces, adversarial attacks, STRIDE methodology, AI vulnerabilities, red teaming, and security testing approaches.
- You will learn about SOC operations, SIEM concepts, incident response, malware analysis, threat investigation, and AI-assisted security operations.
- You will learn security governance, risk management, AI governance, compliance, privacy principles, and responsible AI security practices.
- You will apply cybersecurity skills through an end-to-end AI security project involving threat analysis, AI risk assessment, incident response, and professional security reporting.